BOL: Related items

Gene Ontology Consortium

Jit — Fri, 11 Jan 2019 05:51:02 -0600

The GO knowledgebase is composed of two primary components:

the Gene Ontology (GO), which provides the logical structure of the biological functions (‘terms’) and their relationships to one another, manifested as a directed acyclic graph
the corpus of GO annotations, evidence-based statements relating a specific gene product (a protein, non-coding RNA, or macromolecular complex, which we often refer to as ‘genes’ for simplicity) to a specific ontology term

Together, the ontology and annotations aim to describe a comprehensive model of biological systems. Currently, the GO knowledgebase includes experimental findings from over 140 000 published papers, represented as over 600 000 experimentally-supported GO annotations. These provide the core dataset for additional inference of over 6 million functional annotations for a diverse set of organisms spanning the tree of life.

In addition to this core knowledgebase, GOC resources also include software to edit and perform logical reasoning over the ontologies, web access to the ontology and annotations, and analytical tools that use the GO knowledgebase to support biomedical research.

Address of the bookmark: http://www.geneontology.org/

Predict Gene Ontology with sequences !

LEGE — Wed, 08 Jul 2020 04:59:28 -0500

PANNZER (Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.

PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use AAI-profiler to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.

http://ekhidna2.biocenter.helsinki.fi/sanspanz/

IterPro is for the beginners

h ttps://www.ebi.ac.uk/interpro/

You can find other comparative info at https://academic.oup.com/view-large/118391389

Address of the bookmark: http://ekhidna2.biocenter.helsinki.fi/sanspanz/

CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation

Shruti Paniwala — Thu, 26 May 2022 00:59:49 -0500

CrowdGO is a protein Gene Ontology predictor using a meta approach, analyzing the predictions of other tools in order to get an improved precision and recall.

Please note that the CrowdGO snakemake workflow is currently only tested on Ubuntu. It should work on OSX, but please report any errors to maarten.reijnders@unil.ch or create an issue.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010075

Address of the bookmark: https://gitlab.com/mreijnders/crowdgo

DarkHorse: a method for genome-wide prediction of horizontal gene transfer

Jit — Thu, 22 Jun 2017 07:58:35 -0500

A new approach to rapid, genome-wide identification and ranking of horizontal transfer candidate proteins is presented. The method is quantitative, reproducible, and computationally undemanding. It can be combined with genomic signature and/or phylogenetic tree-building procedures to improve accuracy and efficiency. The method is also useful for retrospective assessments of horizontal transfer prediction reliability, recognizing orthologous sequences that may have been previously overlooked or unavailable. These features are demonstrated in bacterial, archaeal, and eukaryotic examples.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852411/

XAMPP: Starting Apache fail Ubuntu

Ram Yash Pal — Sat, 07 Jun 2014 05:52:35 -0500

Once you install XAMMP on linux, the most common problem you face is Apache failure. To fix the issues please use following command to first stop and then again start it.

sudo /etc/init.d/apache2 stop

sudo /etc/init.d/mysql stop

sudo /etc/init.d/proftpd stop

sudo /opt/lampp/lampp start

PhpMyAdmin “Wrong permissions on configuration file, should not be world writable!”

Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:

Just chmod 0755 the file

sudo chmod 0755 config.inc.php

Genomic Medicine - Bruce Korf (2014)

Tue, 24 Jun 2014 07:58:44 -0500

May 21, 2014 - Current Topics in Genome Analysis 2014 A lecture series covering contemporary areas in genomics and bioinformatics. More: http://www.genome.gov/COURSE2014

GeNeCK (Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks

Rahul Nayak — Tue, 15 Jan 2019 09:39:30 -0600

GeNeCK (Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks based on gene expression data and optional hub gene information.

It efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.

GeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at http://lce.biohpc.swmed.edu/geneck

Address of the bookmark: http://lce.biohpc.swmed.edu/geneck/

PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes

BioStar — Thu, 13 Aug 2020 10:06:19 -0500

PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring O(n2) resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.

Address of the bookmark: https://github.com/ryanmelnyk/PyParanoid

homologizer: Phylogenetic phasing of gene copies into polyploid subgenomes

Abhi — Sat, 03 Jun 2023 19:19:10 -0500

This tutorial describes the usage of homologizer to phase gene copies into polyploid subgenomes. The tutorial is an abbreviated version of a soon-to-be published paper in Methods in Molecular Biology. Please see that paper for many more details and practical considerations for running homologizer analyses. If you use homologizer, please cite the paper in which we first describe the method:

Freyman, W.A., Johnson, M.G., and C.J. Rothfels. 2022. Homologizer: phylogenetic phasing of gene copies into polyploid subgenomes. bioRxiv 2020.10.22.351486v4

homologizer is implemented in RevBayes. Please see http://revbayes.com to download and install RevBayes. For users without previous RevBayes experience, we recommend the tutorials at http://revbayes.com.

Address of the bookmark: https://github.com/wf8/homologizer

Dynamic chromosome breakpoints !!!

Jitendra Narayan — Wed, 13 Aug 2014 18:38:10 -0500

Cell division involves the distribution of identical genetic material, DNA, to two daughters’ cells. During this process, duplicated deoxyribonucleic acid (DNA) goes through a condensation and decondensation process. This is followed by nuclear envelope dissolution, mitotic spindle assembly, migration of the sister chromatid pairs to the metaphase plate, division and segregation of identical sets of chromosomes into daughter nuclei and nuclear envelope reformation.

The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo recombination which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.

During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The “chromosomal breakpoints” refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this “break and sealing/ break and reattach” process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.

Apart from certain chromosome abnormalities, these “crossing over” of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.

I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/ in my next blog.

Software for recombination detection:

RAT http://cbr.jic.ac.uk/dicks/software/RAT/

Breakpointer https://github.com/ruping/Breakpointer

DRP http://web.cbio.uct.ac.za/~darren/rdp.html

RB-finder http://www.ncbi.nlm.nih.gov/pubmed/18707535

LDhat2.0 http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml

Reference:

http://www.nature.com/scitable/topicpage/genetic-recombination-514#

Image: Wikipedia , sciencelearn.org.nz

Recommended Articles:

http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/

http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/

http://learn.genetics.utah.edu/content/disorders/chromosomal/

http://www.ncert.nic.in/html/learning_basket/biology/cc&cd.pdf